Communication Limited Genetic Structure of Gypsy Populations Reflecting a Recent History in Europe

Nikola Lackovi´c 1 , Milan Pernek 1, Coralie Bertheau 2, Damjan Franjevi´c 3, Christian Stauffer 4 and Dimitrios N. Avtzis 5,*

1 Croatian Forest Research Institute, Cvjetno naselje 41, 10450 Jastrebarsko, Croatia; [email protected] (N.L.); [email protected] (M.P.) 2 UMR CNRS-UFC 6249 Chrono-Environment, Université de Franche Comte, 25200 Montbéliard, France; [email protected] 3 Faculty of Science, University of Zagreb, HR-10000 Zagreb, Croatia; [email protected] 4 Department of Forest and Soil Sciences, BOKU, University of Natural Resources and Life Sciences, A-1180 Vienna, Austria; [email protected] 5 Forest Research Institute, Hellenic Agricultural Organization Demeter, Vasilika, 57006 Thessaloniki, Greece * Correspondence: [email protected]; Tel.: +30-2310-461171 (int. 213/221)

 Received: 13 August 2018; Accepted: 17 October 2018; Published: 18 October 2018 

Abstract: The gypsy moth, , a prominent polyphagous species native to Eurasia, causes severe impacts in deciduous forests during irregular periodical outbreaks. This study aimed to describe the genetic structure and diversity among European gypsy moth populations. Analysis of about 500 individuals using a partial region of the mitochondrial COI gene, L. dispar was characterized by low genetic diversity, limited population structure, and strong evidence that all extant haplogroups arose via a single Holocene population expansion event. Overall 60 haplotypes connected to a single parsimony network were detected and genetic diversity was highest for the coastal populations Croatia, Italy, and France, while lowest in continental populations. Phylogenetic reconstruction resulted in three groups that were geographically located in Central Europe, Dinaric Alps, and the Balkan Peninsula. In addition to recent events, the genetic structure reflects strong gene flow and the ability of gypsy moth to feed on about 400 deciduous and conifer species. Distinct genetic groups were detected in populations from Georgia. This remote population exhibited haplotypes intermediate to the European L. dispar dispar, Asian L. dispar asiatica, and L. dispar japonica clusters, highlighting this area as a possible hybridization zone of this species for future studies applying genomic approaches.

Keywords: forest pest; population genetics; population outbreaks; range shift; admixture

1. Introduction The gypsy moth, Lymantria dispar L. (, ), is a polyphagous pest feeding on more than 400 plant species with a preference for species within the Quercus [1]. Lymantria dispar is native to the Palearctic region [1,2] and became invasive in North America after its intentional introduction for hybridization experiments [3]. Currently, L. dispar is considered one of the most notorious forest pests worldwide [4], with outbreaks in its native range being common particularly in the oak forests of the Mediterranean region, while in Asia the broader spectrum of potential hosts renders gypsy moth capable of even more massive outbreaks [5]. Nonetheless, the potential of gypsy moth populations to erupt varies greatly [6] as in cases of recent invasion an outbreak can be sustained [7]. For all these reasons, gypsy moth, has been in the spotlight of various investigations ranging from population dynamics [8] and dispersal ecology [9,10] to the distribution of its genetic

Insects 2018, 9, 143; doi:10.3390/insects9040143 www.mdpi.com/journal/insects Insects 2018, 9, 143 2 of 10 diversity at a global scale [11,12]. Three subspecies are recognized throughout the temperate part of the world due to their economic importance; European (L. dispar dispar) and two Asian (L. dispar asiatica in Russia and Asia and L. dispar japonica in Japan), and each of them is described separately based on morphological and behavioral traits [1]. Nonetheless, the status of the two Asian subspecies still remains disputable [13], as recent molecular investigations argue for an even more elaborate pattern among the far east populations [12]. However, female flight capability turned out to be the most important behavioral trait distinguishing Asian subspecies from European [10,14]. First genetic analysis based on DNA sequences resulted in developing an mtDNA marker that verified the close resemblance of North American and European population, that both were distinctly separated from Asian populations [11]. This pattern was confirmed in subsequent studies which showed that North American populations were related to French populations and additionally that Asian population were separated into a western and eastern genetic entity [14], where Japanese populations form a separate cluster differentiated from Western Asian populations [15]. Until recently, studies on European populations of gypsy moth were mostly integrated into broader investigations that aimed at a global overview of this species [14,15]. A study analyzing Croatian populations revealed a genetic split between coastal and continental populations caused by the Dinaric Alps [16]. In this study we sampled 38 locations from sixteen European countries, and additionally two Georgian populations to reveal insight into the phylogeography and demography of this species in Europe.

2. Materials and Methods Samples (larvae) were collected from 36 localities in sixteen European countries and two additional sites from Georgia between 2010 and 2014 (Table1), with specimens from the same locality/site constituting a geographic population. Larvae were taken from distant trees (not more than one larva per tree) so to avoid any bias induced by the use of mtDNA marker, and after collection they were immediately put into 99% ethanol and stored at −20 ◦C in laboratory. In total, 497 individuals were analyzed. One pair of abdominal legs was used for genomic DNA extraction from each specimen individually, using SIGMA Aldrich mammalian genomic DNA extraction kit (Sigma, St. Louis, MO, USA) and following manufacturer’s instruction. DNA amplification was performed with primers UEA5 and UEA10 [17] in 20 µL reactions containing 2 mM of MgCl2, 100 mM of dNTPs (Fermentas, Vilnius, Lithuania), 0.5 mM of each primer 1U of Taq (Fermentas, Vilnius Lithuania). Thermocycling consisted of an initial denaturation step at 94 ◦C (2 min), which was followed by 33 cycles at 94 ◦C (30 s), 48 ◦C (60 s), and 68 ◦C (60 s), and a final extension step at 68 ◦C (10 min). All reactions were checked for amplification by gel electrophoresis, and confirmed products were purified using peqGOLD Cycle-Pure Kit (PeqLab, Erlangen, Germany) and directly sequenced with UEA10 at Eurofins MWG Operon (Mainz, Germany). Sequences were manually examined using Chromas Lite (Technelysium, Brisbane Australia) and aligned using ClustalW algorithm incorporated in BioEdit [18]. Upon alignment, ends of sequences were trimmed in order to obtain full overlap. Finally, this alignment was used for determination of haplotype sequences, using TCS 1.21 [19]. Singleton sequences were verified by an additional PCR and sequencing. Haplotype sequences were deposited in NCBI with accession numbers: KY628707 to KY628749. Haplotype diversity, nucleotide diversity, mean number of pairwise differences and allelic richness were calculated for each population using ARLEQUIN [20] and Contrib 1.02 [21]. Parsimony network was reconstructed by cladistic analysis in TCS 1.21 and drawn in CorelDraw X5 (Ottawa, ON, Canada). Ambiguities in the cladogram were resolved by applying topological, geographic, and frequency criteria, where applicable [22], while phylogeographic inferences were assessed with ANeCA v1.2 [23]. Overall population differentiation was assessed by testing if NST(obs) was greater than NST(exp) using heuristic permutation test with 1000 replicates in PERMUT 1.0 [24], and subsequently compared with GST in order to assess the depth of differentiation. Insects 2018, 9, 143 3 of 10

Table 1. Countries, localities, WGS84 coordinates in degrees (Lat., Long.), host tree (QE = Quercus petraea; QR = Q. robur; QI = Q. ilex; QP = Q. pubescens; QS = Q. suber; QO = Q. coccifera; FS = Fagus sylvatica; MA = Malus sp.; VAR1 = Q.petraea + F.sylvatica; VAR2 = Q. robur + F. sylvatica; VAR3 = Q. robur + Q. petraea; VAR4 = Q. petraea + Q. pubescens; VAR5 = Salix sp. + Populus sp.; VAR6 = Q. rubra + Q. petraea + Q. cerris + Carpinus betulus + Fraxinus sp.), number of individuals (N), number of haplotypes (HT), haplotype diversity (Hd), nucleotide diversity (π), mean number of pairwise differences (MNPD), and Allelic richness (r) after rarefaction to smallest sample size (5). Mean value and standard deviation (SD) is shown for all genetic diversity indices except for r.

Country Abbrev. Host Lat. Long. N HT Hd ± SD π ± SD MNPD ± SD r (5) Austria AUT1 QE 47.75 16.54 27 5 0.695 ± 0.078 0.001 ± 0.001 0.871 ± 0.632 1.966 Belgium BEL1 FS 50.82 4.41 11 2 0.181 ± 0.143 0.001 ± 0.000 0.727 ± 0.584 0.455 BUL1 QR 43.09 23.46 5 1 0 ± 0 0 ± 0 0 ± 0 0.000 BUL2 QR 41.71 24.16 8 3 0.607 ± 0.164 0.002 ± 0.001 1.357 ± 0.933 1.518 Bulgaria BUL3 QR 42.74 27.74 5 1 0 ± 0 0 ± 0 0 ± 0 0.000 BUL4 QR 43.21 26.62 12 3 0.727 ± 0.058 0.002 ± 0.001 1.939 ± 1.181 1.788 CRO1 QI 44.65 14.47 37 10 0.818 ± 0.038 0.003 ± 0.002 2.087 ± 1.193 2.555 CRO2 QR 45.47 17.99 14 1 0 ± 0 0 ± 0 0 ± 0 0.000 CRO3 QR 44.95 19.07 5 1 0 ± 0 0 ± 0 0 ± 0 0.000 Croatia CRO4 QP 44.15 15.3 19 8 0.859 ± 0.052 0.004 ± 0.002 2.666 ± 1.485 2.815 CRO5 VA1 45.22 16.28 25 6 0.426 ± 0.121 0.000 ± 0.000 0.473 ± 0.425 1.167 CRO6 QR 45.65 15.59 6 2 0.333 ± 0.215 0.000 ± 0.000 0.333 ± 0.380 0.833 CZE1 QE 49.11 17.04 10 4 0.533 ± 0.180 0.001 ± 0.001 0.600 ± 0.519 1.500 Czech CZE2 QR 48.88 17.1 7 2 0.285 ± 0.196 0.000 ± 0.000 0.285 ± 0.340 0.714 Republic CZE3 QE 48.85 16.01 7 3 0.523 ± 0.208 0.001 ± 0.001 0.857 ± 0.681 1.429 FRA1 QS 41.71 9.33 11 3 0.345 ± 0.172 0.000 ± 0.000 0.363 ± 0.377 0.909 FRA2 QP 44.47 2.47 5 2 0.400 ± 0.237 0.000 ± 0.000 0.400 ± 0.435 1.000 France FRA3 QE 47.82 1.92 24 7 0.721 ± 0.070 0.002 ± 0.001 1.554 ± 0.961 2.038 FRA4 QE 44.85 2.12 14 6 0.802 ± 0.090 0.001 ± 0.001 1.219 ± 0.824 2.500 GEO1 MA 41.94 44.48 11 3 0.618 ± 0.103 0.008 ± 0.005 5.818 ± 3.013 1.407 Georgia GEO2 MA 41.88 46.13 6 3 0.733 ± 0.155 0.005 ± 0.003 3.933 ± 2.290 1.833 GER1 VA2 48.26 7.76 20 6 0.636 ± 0.115 0.001 ± 0.001 1.194 ± 0.797 1.838 Germany GER2 VA3 49.91 10.19 26 6 0.566 ± 0.108 0.001 ± 0.001 1.141 ± 0.764 1.579 GER3 QE 51.91 14.35 8 1 0 ± 0 0 ± 0 0 ± 0 0.000 GRE1 QO 40.77 23.11 31 3 0.127 ± 0.079 0.000 ± 0.000 0.193 ± 0.250 0.323 GRE2 QO 41.08 23.54 12 2 0.303 ± 0.147 0.000 ± 0.000 0.303 ± 0.336 0.682 Greece GRE3 QO 38.63 22.97 5 1 0 ± 0 0 ± 0 0 ± 0 0.000 GRE4 QO 41.12 25.41 9 2 0.500 ± 0.128 0.001 ± 0.001 1.000 ± 0.739 0.952 Holland HOL1 QR 51.98 5.68 9 3 0.555 ± 0.165 0.000 ± 0.000 0.611 ± 0.530 1.389 HUN1 VA4 47.83 19.96 10 4 0.533 ± 0.180 0.001 ± 0.001 0.800 ± 0.628 1.500 Hungary HUN2 VA5 47.71 17.12 11 4 0.709 ± 0.099 0.001 ± 0.001 0.872 ± 0.661 1.851 HUN3 VA6 47.07 17.34 5 2 0.600 ± 0.175 0.000 ± 0.000 0.600 ± 0.562 1.000 ITA1 QI 42.99 10.5 25 5 0.776 ± 0.046 0.002 ± 0.001 1.513 ± 0.941 2.245 Italy ITA2 QS 40.51 8.46 14 3 0.483 ± 0.142 0.000 ± 0.000 0.527 ± 0.467 1.209 FYROM MAC1 N/A 41.36 21.21 7 4 0.809 ± 0.129 0.002 ± 0.001 1.714 ± 1.131 2.381 Poland POL1 VA5 53.29 22.61 15 3 0.361 ± 0.144 0.001 ± 0.001 0.590 ± 0.500 0.905 Romania ROM1 N/A 44.5 23.74 14 1 0 ± 0 0 ± 0 0 ± 0 0.000 Serbia SER1 QE 44.47 5.57 7 3 0.523 ± 0.208 0.001 ± 0.001 0.857 ± 0.681 1.429

To separate the source of variation in three hierarchical levels (among groups of populations (FCT), among populations within groups (FST), and within populations (FSC)), objective grouping and Analysis of Molecular Variance were performed using ARLEQUIN [19] based on the host of each population (Table1). The best-fit nucleotide substitution model of our data was selected among 88 different models (in this case GTR with Gamma distributed heterogeneity of rates) as implemented Insects 2018, 9, 143 4 of 10 in jModeltest 2.1.7 [25], and this model was then used in MrBayes 3.2 [26]. Two separate chains were run in the Bayesian analysis, and the initial run lasted 2 × 106 generations, with a sampling frequency of 100 generations in order to define the trees to be discarded in the second run. As a plateau between standard deviations was reached after 5 × 105 generations, 500 trees were discarded from the estimation of the consensus tree. To better understand the assignment of haplotypes in clades and their geographic distribution, we also used sequences deposited in NCBI GenBank from previous investigations of L. dispar (HM013724 (Russia, Vostochnyy), HM013736 (Japan), HM013737 (Japan) [15]; KX436205 (Japan, Honshu), KX436223 (Japan, Nagano), KX436230 (Russia, Vladivostok) [27]; KY923059 (Russia, Primorski), KY923063 (Lithuania), KY923064 (Russia, Krasnoyarsk), KY923065 (Kazhakstan), GU994784 (Mongolia) [28]). Locality map and haplotype distribution map were constructed using ArcMap 9. 3 (ESRI, Redlands, California, USA) and Genetic Landscape Toolbox [29] and arranged in CorelDraw X5 (Ottawa, ON, Canada). Finally, haplotype rarefaction analysis was constructed using R3.2.3 [30] with the function specaccum of the vegan package [31].

3. Results In total, 497 sequences 676 bp long (spanning from 699 to 1375 bp of L. dispar COI sequence) were used for further analyses. Cladistic analysis resulted in 60 haplotypes (Figure1) distinguished by 25 singletons and 19 parsimony informative polymorphic sites, with the rarefaction curve of haplotypes reaching a plateau (data not shown) showing that the sampling effort was sufficient to describe intraspecific haplotype diversity [32]. Total haplotype diversity HT was 0.81 and intrapopulation diversity HS was 0.437 (data not shown). The lowest genetic diversity values were spotted in populations from the continental basin of the Balkan Peninsula between Dinaric Alps, Alps and Carpathian Alps and in northern Continental regions. On the other hand, the highest genetic diversity was observed in Coastal Croatia, Italy, and France. Populations from the Aegean coast and Black sea coast showed rather low diversity, while populations from Georgia showed intermediate values (Table1). Fixation index GST (se) = 0.463 (0.056) was smaller than observed fixation index NST(obs.) (se) = 0.521 (0.059) which was significantly greater than theoretical fixation index NST(theor.) (se) = 0.456 (0.001) (p = 0.010), confirming the existence of a limited phylogeographic structure (GST < NST(obs.) > NST(theor.)) (Figure2). Nevertheless, AMOVA attributed not more than 24% of divergence to host selection (FCT=0.23831, p < 0.01), with the main source of divergence being found among populations within groups (FST = 0.53239, p < 0.01), and within populations (FSC = 0.38609, p < 0.01), rejecting the hypothesis of host-driven divergence at least among the broadleaved hosts analyzed in the current study. The phylogenetic tree grouped European haplotypes in a similar pattern supporting the main clades with posterior probabilities higher than 80%, with the exception of green cluster that was the most common one in Central Europe. The inclusion of NCBI GenBank sequences from Asia, revealed the position of haplotypes LD52, LD53, and LD54 from Georgia diverged 1.46% from the European groups, while averagely diverged 0.86% from the cluster of Asian haplogroups L. dispar asiatica/L. japonica haplotypes (KX436223, KY923509, HM013724, GU994784, HM013737, HM013736, KX436205, KX436230) retrieved from NCBI (Figure3). Finally, while Siberian sequences integrated in the European L. dispar dispar cluster, Georgian haplotypes formed a distinct clade, separated from L. dispar japonica and L. dispar asiatica. Insects 2018, 9, 143 5 of 10 Insects 2018, 9, x FOR PEER REVIEW 5 of 10 Insects 2018, 9, x FOR PEER REVIEW 5 of 10

FigureFigureFigure 1. 1. Parsimony Parsimony networknetwork reconstructed byby cladistic cladistic analysis analysis with withwith 95% 95% connection connection limit limitlimit using usingusing TCS TCSTCS 1.21.1.21.1.21. NumbersNumbers Numbers representrepresent thethe haplotypes.haplotypes. Dimensions Dimensions of of pies pies are are proportional proportional to to frequency, frequency, and andand each eacheach haplotypehaplotypehaplotype isis is coloredcolored colored based basedbased onon itsits affiliationaffiliation toto aa certaincertain clade. clade.

FigureFigure 2. 2.Haplotype Haplotype distributiondistribution of Lymantria dispar inin Europe. Europe. Colored Colored circles circles represent represent the the clades clades accordingFigureaccording 2. Haplotype to to parsimony parsimony distribution network network (Figure (Figureof Lymantria1), 1), acronyms acronyms dispar indicate in indicate Europe. localities localities Colored (Table (Table circles1) and 1) represent and dimension dimension the of clades pies of areaccordingpies proportional are proportionalto parsimony to sample tonetwork sizesample and (Figure haplotypesize and 1), acronyms abundance.haplotype indicate abundance. Underlaying localities Underlaying map (Table represents 1) mapand biogeographic dimensionrepresents of regionspiesbiogeographic are of proportional Europe regions [33]. of Theto Europe sample figure [33]. was size The constructed and figure ha wasplotype using constructed ArcMapabundance. using 10.1 ArcMap (ESRI,Underlaying Redlands, 10.1 (ESRI, map CA, Redlands, represents USA). biogeographicCA, USA). regions of Europe [33]. The figure was constructed using ArcMap 10.1 (ESRI, Redlands, CA, USA).

Insects 2018, 9, 143 6 of 10 Insects 2018, 9, x FOR PEER REVIEW 6 of 10

Figure 3. Bayesian reconstruction of molecular phylogen phylogeneticetic relationships among haplotypes of of the currentcurrent researchresearch supplemented supplemented with with sequences sequences submitted submitted in GenBank in GenBank (see text for(see detailed text for description). detailed description).Numbers above Numbers nodes represent above nodes the Bayesian represent posterior the Bayesian probability posterior with probability values greater with than values 0.6. Colorgreater of thaneach 0.6. bar Color is identical of each to bar the onesis iden usedtical in to Figure the ones1. used in Figure 1.

4. Discussion Discussion Gypsy moth is a holarctic species, flexible flexible in terms of temperature tolerance [34] [34] and it has extremely wide spectrum of host plants [[35].35]. Th Thisis species species successfully successfully invaded invaded a a vast vast variety variety of of ecosystems, causing disturbances on a wide array of tree tree and and general general plant plant species. species. Model Model predictions predictions forfor L. dispar dispar support a a range shift of up to 900 km northwards in Europe as a consequence of increaseincrease in average average air air temperature temperature [36]. [36]. Therefore, Therefore, it it is is important important to to understand understand the the phylogeography phylogeography of L. dispar dispar in Europe regarding management strategiesstrategies [[37].37]. Major [[38–40]38–40] andand minorminor refugia refugia [ 27[27,41],41] during during ice ice ages ages coupled coupled with with recent recent gene gene flow flow events events [42] [42]determined determined the currentthe current pattern pattern of divergence. of divergence. Though Though for some for some species species it has it beenhas been demonstrated demonstrated that thatthe mostthe most recent recent ice age ice hadage thehad most the most profound profound impact impact on intraspecific on intraspecific diversity diversity [43], for[43], several for several other otherspecies species the origin the origin of divergence of divergence goes furthergoes furt backher beforeback before the last the ice last age ice [44 age,45 ],[44,45], with Lymantria with Lymantria dispar disparbeing being one of one them of them [13]. [13]. Intraspecific Intraspecific divergence divergence among among haplotypes haplotypes of of European EuropeanL. L. dispardispar dispar (0.5029%) isis congruentcongruent with with previous previous findings findings that that this this clade clade arose arose around around 200 200 thousand thousand years years (kyr) (kyr) [13]. [13]. In particular, the observed genetic pattern of L. dispar dispar in Europe seems to have been shaped by at least two refugia, one located near the Carpathian Mountains (green) spreading to Central

Insects 2018, 9, 143 7 of 10

In particular, the observed genetic pattern of L. dispar dispar in Europe seems to have been shaped by at least two refugia, one located near the Carpathian Mountains (green) spreading to Central Europe and the Pontic-Mediterranean region (blue) spreading to the Balkans and the north of Europe. Furthermore, it is likely that contemporary pattern of gypsy moth phylogeography in Europe was also influenced by anthropogenic migration. This has been already hypothesized in the recent study of the Asian gypsy moth based on COI barcode sequences [46] that revealed an unusually close relationship between geographically distant haplotypes which could not be explained merely by natural dispersal of gypsy moth. Being a highly polyphagous species, L. dispar populations would have been expected to exhibit deep intraspecific divergence as different selection pressures are associated with different host plants, something that favors the emergence of barriers to gene flow [47,48]. Should these barriers be maintained for a sufficiently long period of time, they may lead to the formation of distinct host-associated lineages [49]. This concept was initially thought to be valid mostly for parthenogenetically reproducing species [50–52], yet recent studies have shown that it is also evident in sexually reproducing species [49,53]. However, the limited genetic structure revealed among gypsy moth populations in Europe coupled with the AMOVA outcome do not support this expectation. As with other polyphagous species such as Pityogenes chalcographus [54] or Heliconius melpomene [55,56] life-history traits might have evolved on one host plant upon secondary contact could have been transmitted to populations feeding on a different host species, and thus render the herbivore insect species capable to feed on different host species [54]. Furthermore, this effect is reinforced by the high gene flow of L. dispar as the combination of the migratory pathways (flying , wind-borne dispersal of neonate larvae and long distances anthropogenic movement [9]) could facilitate the redistribution and coalescence of populations [57].

5. Conclusions Despite the relatively large sample, we were able to determine only limited inferences of phylogeographic structure among localities in Europe, with at least two refugial areas contributing to the current genetic structure of gypsy moth. The near panmictic status of haplotype LD4 also present in Georgia suggests that more complex forces have taken role in shaping of the contemporary phylogeographic pattern of gypsy moth, and one of likely explanations could be a man-aided dispersal. Such hypotheses have already been drawn on larger scale studies [46]. However, the separation of the Georgian populations from other European populations, but also from the Asian haplotypes L. dispar asiatica and L. dispar japonica, shows that there are likely many more genotypic entities than recently described [28]. In fact, as differences in biology and behavior are described between gypsy moths from Europe and Asia, i.e., flight capability of females [10,58], the region of the Caucasus should be studied more thoroughly in order to examine the taxonomic status of the genetic entities in that geographic area.

Author Contributions: N.L. is a postdoc responsible to introduce and implement research of forest pests and diseases by means of molecular biology in Division of Forest Protection and Game Management at Croatian Forest Research Institute. The author team forms part of a consortium of a research project on defoliators as invasive forest pests in changing climate conditions (DIFPEST), coordinated by M.P. C.S., and M.P. conceived the ideas; N.L., D.N.A., and C.B. conducted experiments. N.L., C.B., and D.N.A. analyzed data. All authors contributed to the writing. Funding: This research was partly funded by Croatian Science Foundation project HRZZ 7616 DIFPEST, and Bilateral scientific and technical cooperation project funded by Croatian Ministry of Science and ÖAD. This study was also supported by the Austrian Science Fund FWF project I2604-B25. Acknowledgments: We thank Nicolas Meurisse, Jaroslav Holuša, Alain Roques, Horst Delb, Gabriela Lobinger, György Csóka, Milka Glavendeki´c, Ferenc Lakatos, Daniela Kirilova Pilarski, Leen Moraal, Pio Federico Roversi, Michele Squarcini, Gernot Hoch, Mario Contarini, Irena Papazova, Sterja Naceski, Constantin Netoiu, Medea Burjanadze, and Andreas Linde for generous help in sampling. We also thank to Susanne Kumböck, Hannes Schuler and Blaženka Ercegvac for help in the laboratory and Vassiliki Sgardeli, George I. Memtsas, and Nikolaos Fyllas for their assistance with R programming. Insects 2018, 9, 143 8 of 10

Conflicts of Interest: The authors declare no conflict of interest.

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